The Endless Frontier
and
The Thinking Machine
Hans P. Moravec
Artificial Intelligence Lab
Computer Science Dept.
Stanford University
Stanford, Ca. 94305
Copyright 1978 by Hans P. Moravec
All Rights Reserved
The first modern computers, appearing in the late 1940's,
offered unprecedented opportunities for experiments in complexity.
They raised the hope in influential scientists like John von Neumann
and Alan Turing that the ability to think, our greatest asset in
dealing with the world, might soon be understood well enough to
duplicate. Our minds might be amplified just as our muscles had been
by energy machines.
Computers have become vastly more capable since then, but are
still much stupider than people in most areas. Not for lack of trying.
The last decade, in particular, has seen thousands of people years
devoted directly to making them smarter. Much effort has been
expended on computer programs which do mathematics, computer
programming and common sense reasoning, are able to understand natural
languages and interpret scenes seen through cameras and spoken
language heard through microphones and to play games humans find
challenging.
There's been some progress. Arthur Samuel's 20 year old
checker program occasionally beats checker champions, and chess
programs have played at good amateur (class B) level for nearly as
long. In August of 1978 a chess program written by David Slate and
Larry Atkin of Northwestern University won one serious game and tied
another against David Levy, a chess International Grandmaster. It
happened in a tournament to settle a 1968 bet between Levy and several
computer scientists that a computer couldn't beat him within a
decade. Levy won the tournament and the bet, but by a narrower margin
than he expected. An earlier version of the Northwestern program won
the Minnesota Open Chess Championship in March 1977, earning a chess
rating in the expert range. The program owes much of its success to
the computer it runs on, a CDC Cyber 176. Executing 14 million
instructions per second it is about 10 times faster than prior
machines used to play chess.
A ten year effort at MIT has gathered specialized knowledge
about algebra, trigonometry, calculus and related fields from many
sources into a wonderful program called MACSYMA. MACSYMA manipulates
symbolic formulas the way pocket calculators manipulate numbers. With
it a person can, for instance, solve a differential equation without
thinking about the mechanics of doing an integral in the same way that
someone with a pocket calculator can find the quotient of two numbers
without knowing about long division. MACSYMA has been used by many to
solve problems that would otherwise have been left untouched.
Other semi-intelligent programs showing up in the real world
can understand simplified typewritten English about restricted
subjects, make elementary deductions in the course of answering
questions and interpret spoken commands chosen from hundred word
repertoires. Some can do simple visual inspection tasks, such as
deciding whether or not a screw is at the end of a shaft.
Computers are at their worst trying to do the things most
natural to humans, like seeing, hearing, language and common sense
reasoning. Large portions of our nervous systems are dedicated to
these skills, and computers are unlikely to match human performance
until they can process as much data as the neural centers. I
calculate that a typical present day computer is a million times less
powerful than a human brain. The computer can perform a million simple
steps per second, but the 40 billion neurons in a brain can switch a
thousand times in the same interval. The spectacular, continuing
evolution of microelectronics should make the requisite power
available at great cost in a decade, and inexpensively by the end of
the century.
In addition to being powerful enough, a computer able to
perform like a human must be properly programmed. Just how long before
the right programs are written is a matter of controversy. Many
critical experiments can't be done now because computers are too small
and too slow. I feel that infusing an adequately powerful machine with
near-human intelligence is not as hard as some guess.
Evolution has independently produced moderate intelligence
several times, indicating that it develops naturally and does not
require improbable leaps. The difficulty can be gauged by the
evolutionary timescale. 300 million years passed between the
invention of the neuron and development of the worm, a similar period
between worms and dumb vertebrates, and 300 million more between
vertebrates and us. Our technology has paralleled nature in many
respects. It had developed electronic switching by 1920, electronic
computers by 1950, and semi-intelligent machines by 1980. By analogy
we ought to have truly smart machines by 2010.
Human equivalent computers will have a profound effect on the
nature and pace of space colonization. People are not built to live in
space, but must be supported by massive, Earth simulating machinery to
remain healthy. Robots can be made without this handicap. Tiny space
probes cruise unprotected through the Solar System, their functioning
unimpaired by vacuum, radiation and temperature extremes. Machines
with these advantages and with human or above human intelligence have
an overwhelming edge in space industrialization. We may be able to
keep up, but only by profoundly changing ourselves.
Natural Intelligence
My optimism about the future of intelligent machines is based
partly on the evolutionary record. Nature holds the patents on high
intelligence. It invented it not once, but several times, as if to
demonstrate how easy it was.
A billion years ago, before brains or eyes were invented, when
the most complicated animals were something like hydras, double layers
of cells with a primitive nerve net, our progenitors parted company
with the invertebrates. Now both clans have intelligent members.
Cephalopods are the most intellectual invertebrates. Most
mollusks are sessile shellfish, but octopus and squid are highly
mobile, with big brains and excellent eyes. Evolved independently of
us, they are different. The optic nerve connects to the back of the
retina, so there is no blind spot. The brain is annular, a ring
around the esophagus. The green blood is circulated by a systemic
heart oxygenating the tissues and two gill hearts moving depleted
blood. Hemocyanin, a copper doped protein related to hemoglobin and
chlorophyll, carries the oxygen.
Octopus and their relatives are swimming light shows, their
surfaces covered by a million individually controlled color changing
cells. A cuttlefish placed on a checkerboard can imitate the pattern,
a fleeing octopus can make deceiving seaweed shapes coruscate backward
along its body. Photophores of deep sea squid, some with irises and
lenses, generate bright multicolored light. Since they also have good
vision, there is a potential for high bandwidth communication.
Their behavior is mammal like. Octopus are reclusive and shy,
squid are occasionally very aggressive. Small octopus can learn to
solve problems like how to open a container of food. Giant squid,
with large nervous systems, have hardly ever been observed except as
corpses. They might be as clever as whales.
Time before present Representative Creatures Significant events
0 (you are here) | | | | | computers massive technology
2.5 million years | | | | | |
10 | | | | elephants | tool use
| | | whales | primates
40 | | | | | |
| | | | | |
90 octopus squid | | | |
| | | +-----+-----+
160 +---+---+ birds mammals
| | | learned behavior
250 early squid +------+------+ warm bloodedness
| reptiles
360 | |
cephalopods fish |
490 | | amphibians land vertebrates
+---+ +----+---+
640 mollusks vertebrates
| |
810 | | complex nerve centers
+------+------+
1 billion years | invention of the neuron
| old age death
1.21 | sex in animals perfected
|
1.44 | multi-cellular animals
animals
1.69 |
plants |
1.96 | | oxygen to support animals
+----+
2.25 |
|
2.56 blue-green | nucleated cells
algae |
2.89 +-------+
| DNA genetics?
3.24 | photosynthesis
earliest cells reliable reproduction
3.61 | invention of the cell
| inorganic protein microspheres
4 billion years non-living chemicals amino acid formation
FIGURE: Highlights in the evolution of terrestrial intelligence.
The distance along the edge of the tree is proportional
to the square root of the time from the present. This
seems to space things nicely.
Birds are vertebrates, related to us through a 300 million
year old, probably not very bright, early reptile. Size-limited by
the dynamics of flying, some are intellectually comparable to the
highest mammals.
The intuitive number sense of crows and ravens extends to
seven, compared to three or four for us. Birds outperform all mammals
except higher primates and the whales in "learning set" tasks, where
the idea is to generalize from specific instances. In mammals
generalization depends on cerebral cortex size. In birds forebrain
regions called the Wulst and the hyperstriatum are critical, while the
cortex is small and unimportant.
Our last common ancestor with the whales was a primitive
rat-like mammal alive 30 million years ago. Some dolphin species have
body and brain masses identical to ours, and have had them for more
generations. They are as good as us at many kinds of problem solving,
and can grasp and communicate complex ideas. Killer whales have
brains seven times human size, and their ability to formulate plans is
better than the dolphins', who they occasionally eat. Sperm whales,
though not the largest animals, have the world's largest brains.
Intelligence may be an important part of their struggle with large
squid, their main food.
Elephant brains are five times human size. Elephants form
matriarchal tribal societies and exhibit complex behavior. Indian
domestic elephants learn over 500 commands, and form voluntary mutual
benefit relationships with their trainers, exchanging labor for baths.
They can solve problems such as how to sneak into a plantation at
night to steal bananas, after having been belled (answer: stuff mud
into the bells). And they never forget (really).
Apes are our 10 million year cousins. Chimps and gorillas can
learn to use tools and to communicate in human sign languages at a
retarded level. Chimps have one third, and gorillas one half, human
brainsize.
Nervous System Size and Intelligence
Animals exhibiting near-human behavior have hundred billion
neuron nervous systems. Imaging vision alone requires a billion. The
smartest insects have a million brain cells, while slugs and worms
make do with a thousand, and sessile animals with a hundred. The
portions of nervous systems for which tentative wiring diagrams have
been obtained, including nearly all of the large neuroned sea slug,
Aplysia, the flight controller of the locust and the early stages of
vertebrate vision, reveal neurons configured into efficient, clever,
assemblies.
Measuring Processing Power
The vertebrate retina has been studied extensively. Its 20
million neurons take signals from a million light sensors and combine
them in a series of simple operations to detect things like edges,
curvature and motion. Then image thus processed goes on to the much
bigger visual cortex in the brain.
Assuming the visual cortex does as much computing for its size
as the retina, we can estimate the total capability of the system.
The optic nerve has a million signal carrying fibers and the optical
cortex is a thousand times deeper than the neurons which do a basic
retinal operation. The eye can process ten images a second, so the
cortex handles the equivalent of 10,000 simple retinal operations a
second, or 3 million an hour.
An efficient program running on a typical computer can
simulate a retinal operation in about two minutes, for a rate of 30
per hour. Thus seeing programs on present day computers seem to be
100,000 times slower than vertebrate vision.
Another measurement
To compare the processing power of brains and computer
programs more generally, note that devices which compute (or think) do
things unexpectedly. Predictable entities like rocks do no
computation, pocket calculators do a little, bees do a lot, and humans
do even more. By this criterion the amount of computing done by a
device is in the mind of the beholder. If you were very good at mental
arithmetic and could predict a calculator's answer before it gave it,
the calculator would do no real computation for you, and might as well
be a rock.
Information theory can make this idea precise. If an entity
in a given state can change to one of N next states with equal
probability, the information in the transition, which I will call the
Compute Energy, is given by
Compute Energy = log2 N
where N is the number of next states. The measure is in binary digits,
bits. Similarly the total compute energy of the entity is the log of the
number of distinct states it can ever be in. Some people call this the
memory size.
A machine that computes faster is more powerful than a slower
one. Compute Power is found by dividing the compute energy of a state
transition by the time required for the transition.
Compute Power = log2 N / t
The units are bits/second.
Slightly more complicated formulas, which give lower values,
apply if the transitions probabilities and times are not all equal.
These measures are highly analogous to the energy and power
capacities of a battery. The compute power and energy of a system of
two or more independent machines is the sum of the individual powers
and energies. A device with a high power, able to reach a moderate
number of states in a short time, can yet have a low energy, if the
total number attainable in the long run is not high. Speeding up a
machine by a factor of n increases the power by the same factor. A
completely predictable system has zero power and energy.
Computer Power
The PDP-10 computer used by many researchers obeys simple
instructions at the rate of one million per second. An instruction
contains one of 2^5 different commands, involving one of 2^4
accumulators and one of 2^18 memory locations, most of these
combinations resulting in distinct next sates. This gives a Compute
Power of
log2 (2^5 x 2^4 x 2^18) bit/(10^-6 sec) = 27 x 10^6 bit/sec
The power is reduced because different instruction sequences can
result in the same outcome and increased by information flowing in
from high speed storage devices connected to the computer for a net of
about 10^7 bit/sec.
The power is also limited by the total compute energy, which
is about 10^7 bits. The PDP 10 could execute at its maximum
effectiveness for one second before reaching a state which could have
been arrived at more quickly another way. Connecting the computer to
the external world can increase this time indefinitely.
14| sperm whale *
10 |
| human *
13| chimp *
10 |
| human vision *
12|
10 |
|
11| proposed NASA wind +
10 | tunnel simulator
|
10|
10 |
|
9 | Cray 1 +
10 | bee *
| CDC 7600, IBM 360/195 +
8 |
10 |
Power |
7 | PDP-10 +
bit 10 |
--- |
sec 6 |
10 | slug *
|
5 |
10 | * living sponge
|
4 |
10 |
|
3 |
10 | + pocket calculator
|
+---------------------------------------------------------------------------
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
Energy (bits)
FIGURE: Compute Power and Energy of various devices. Scales are
logarithmic. The Cray machine is an extremely fast and large
scientific computer. The NASA simulator would probably be a general
purpose computer 100 times as powerful as the biggest existing
machines. It has not been designed yet.
Brain Power
Making a number of simplifying assumptions, the human brain
has 40 billion neurons, each able to change state 1000 times a second.
Considering the space of all possible interconnections of these 40
billion (treating this as the search space natural evolution had, in
the same sense that all possible programs are available to someone
trying to make a computer smart), we note that the number of
combinations reachable from a given state is 2^(40x10^9), giving a
compute power of
40 x 10^9 bit / 10^-3 sec = 40 x 10^12 bit/sec
which is about a million times more than a PDP-10 program. This ratio
agrees with the visual system calculation, because the visual cortex
is about ten percent of the brain.
We got our figure by comparing all possible brain
interconnections with all possible PDP-10 programs, measuring the
relative computational richness of the media available to nature and a
programmer. We concluded that a million PDP-10's would be needed to
support a program that thinks like a human. But a computer can be
reprogrammed more conveniently than a brain can be rewired, and this
is a source of hidden power. The human-equivalent program on a
million machine system could be replaced by single-minded programs to
play superhuman chess or blindingly solve differential equations, an
option not available with a real human.
This generality has a price. The PDP-10 computer is just one
instance of all possible ways of connecting its components. The extra
options give the raw circuitry about 1000 times the compute power of
the finished computer.
But there's a tradeoff between efficiency and design effort.
It's much easier, faster and cheaper to write a program than to build
a circuit for a complex function. Computer instructions do useful
things with few unexpected side effects. In circuit design the basic
operations are more primitive, and the side effects many. A program
that can be written in a few days by one person may take months to
implement in special hardware. It's for this reason that the best
machine chess player is a general purpose computer rather than a
special gadget. I imagine that the first near-human machines will
similarly be implemented on general purpose computers, and converted
later into more efficient hardware.
The Growth of Processing Power
A millionfold increase in processing power seems a tall order,
but the gap is not quite as wide as our simple analysis implies.
PDP-10 computers, still used, are a decade old. Today's
similarly priced machines are ten times as fast. And for ten million
dollars one can buy scientific computers with more than 100 times the
speed. 10,000 of these supercomputers operating together with the
right program should be as intelligent as a human. At a hundred
billion dollars, it's an offer easily refused.
The cost of computing has dropped steadily since the 1950's by
a factor of ten every five years. Each price drop expanded the market
and fueled further advances. In the last few years computers have
crept into the consumer area, disguised as calculators, watches, smart
appliances and automotive electronics.
Computer use will continue to expand in the forseeable future.
The conventional applications of micro-computers will continue to
grow. Calculators and computer games will merge with television and
the phone system to become a universal information utility, giving
bidirectional access to the world's knowledge.
Until now assembly line robots have been deaf, blind and very
dumb. Like the sorcerer's apprentice's broomsticks, they repeated a
sequence of motions over and over, oblivious to the world. Computers,
seeing through cameras and feeling with switches and strain gauges,
are begining to provide the senses and the sense robots have lacked.
As they become more capable and cheaper, and human labor becomes more
expensive, they will be increasingly in demand. Not only the number of
computers, but the capability of each one, will grow.
Homes are less structured than assembly lines, and home robots
are more difficult to make, but they will appear, and be in great
demand, when computers become smart enough. They will be cheap partly
because other robots will assemble them.
Outer space is prime grazing land for machinery. Robot mines
and robot factories making more robots on the moon or in the asteroids
ought to be a fast growing and lucrative investment, once the machines
are good enough.
Integrated circuit technology is nowhere near its physical
limits, and the science to support a few decades of continuing
improvement already exists. In production are new semiconductor
techniques, I^2L, ten times as efficient as older TTL, and super fast
D-MOS, CCD for large sensors and fast bulk memory, and magnetic
bubbles for mass storage. The new 65K memory chips use V-MOS, where
transistors trade depth in the silicon for surface area, pointing
towards much denser three dimensional circuits. The structures on IC
surfaces are becoming smaller than one micron, and electron beams and
X-rays are displacing longer wavelength light in their manufacture.
Industrial and university labs are full of potential major
improvements. Exotic semiconductors like gallium arsenide can be made
into IC's several times faster than silicon. Thermal disturbances
show up as electrical noise, and the amount of energy needed to
unambiguously signal a circuit is proportional to its
temperature. Cooling semiconductor circuits to liquid nitrogen
temperatures allows them to deal with much smaller signals, and
consequently be smaller and less power hungry, and up to 100 times
faster. If we go to 4 degree absolute liquid helium temperatures, even
more astounding things are possible. A Josephson junction gate is a
superconducting logic element in which the magnetic field of one
current can switch off another supercurrent tunneling through a very
thin insulator. The transition takes as little as a picosecond, 1000
times faster than existing semiconductors. Josephson junctions use
1000 times less energy per switching function than neurons.
New discoveries, unpredictable in detail, will further fuel
the fire. Magnetic monopoles weighing 1000 protons, as yet
undiscovered because they are so massive and hard to make, could
drastically expand our options. Matter made of monopole atoms would
be extremely dense and strong, and solid state magnetic circuits could
be millions of times faster than conventional electronics. The lowest
transition in a magnetic atom is so energetic that monopole wire would
magnetically superconduct at the plasma temperatures of conventional
matter.
The cost of computing will continue to fall, by a factor of
10,000 in the next 20 years, and a ten milion dollar general purpose
computer powerful enough to be programmed for human equivalence will
be exist by the 21st century. But that's not the whole story.
In measuring the processing power of the PDP-10 we assumed it
could do nothing but obey its instructions. Processing power expresses
the possibilities per unit time, and this restriction was
expensive. If we instead think about rewiring the computer's
circuitry, the number of options is much greater, and the processing
power is about 1000 times as large. Or, carrying it to absurdity, if
we considered how the atoms of the PDP-10 could be reconfigured, the
compute power would be astronomical.
Hardware design is becoming more automated. Most new
computers, and all new integrated circuits, were designed with the
help of other computers. Programs exist that make printed circuit or
IC patterns from circuit diagrams, and others can simulate designs and
check for errors. As computers get smarter these automatic design
aids will get better, and the complexity bounds on special hardware
will rise.
Some specialized operations useful for human equivalence are
already in hardware. Hughes has built an IC that locates edges in TV
images a hundred times faster than typical programs. Some air traffic
control systems have associative memory units able to look up data
dozens of times more quickly than an unaided computer. Within twenty
years this kind of development, coupled with the general cost
reductions, should allow human equivalent machines costing a year's
salary.
Even before then idiot savant machines like the
Northwestern/CDC chess computer mentioned earlier, better than humans
at a few things, though stupider on the whole, will be slaving for our
short term well being, and long term obsolescence. It has already
begun.
The Future
What happens when increasingly cheap machines can replace
humans in any situation? What will I do when a computer can write this
article, and do research, better than me? These questions face some
occupations now. They will affect everybody in a few decades.
By design, machines are our obedient and able slaves. But
intelligent machines, however benevolent, threaten our existence
because they are alternative inhabitants of our ecological niche.
Machines merely as clever as human beings will have enormous
advantages in competitive situations. Their production and upkeep
costs less, so more of them can be put to work with given
resources. They can be optimized for their jobs, and programmed to
work tirelessly.
Intelligent robots will have even greater advantages away from
our usual haunts. Very little of the known universe is suitable for
unaided humans. Only by massive machinery can we survive in outer
space, on the surfaces of the planets or on the sea floor. Smaller,
intelligent but unpeopled, devices will be able to do what needs to be
done there more cheaply. The Apollo project put people on the moon
for forty billion dollars. Viking landed machines on Mars for one
billion. If the Viking landers had been as capable as humans, their
multi-year stay would have told us much more about Mars than we found
out about the moon from Apollo.
As if this weren't bad enough, the very pace of technology
presents an even more serious challenge. We evolved with a leisurely
100 million years between significant changes. The machines are making
similar strides in decades. The rate will quicken further as
multitudes of cheap machines are put to work as programmers and
engineers, with the task of optimizing the software and hardware which
makes them what they are. The successive generations of machines
produced this way will be increasingly smarter and cheaper. There is
no reason to believe that human equivalence represents any sort of
upper bound. When pocket calculators can out-think humans, what will
a big computer be like? We will simply be outclassed.
Then why rush headlong into the intelligent machine era?
Wouldn't any sane human try to delay things as long as possible? The
answer is obvious, if unpalatable on the surface. Societies and
economies are as surely subject to evolutionary pressures as
biological organisms. Failing social systems wither and die, to be
replaced by more successful competitors. Those that can sustain the
most rapid expansion dominate sooner or later.
We compete with each other for the resources of the accessible
universe. If automation is more efficient than hand labor,
organizations and societies which embrace it will be wealthier and
better able to survive in difficult times, and expand in favorable
ones. If the U.S. were to unilaterally halt technological development,
as a vociferous minority urges, it would soon succumb either to the
military might of the Soviets, or the economic success of its trading
partners. Either way the social ideals which led to the decision would
become as unimportant on the world scale as the opinions of the
religious cults.
If, by some evil and unlikely miracle, the whole human race
decided to eschew progress, the long term result would be almost
certain extinction. The universe is one random event after another.
Sooner or later an unstoppable virus deadly to humans will evolve, or
a major asteroid will collide with the earth, or the sun will go nova,
or we will be invaded from the stars, or a black hole will swallow the
galaxy.
The bigger, more diverse and competent a culture is, the
better it can detect and deal with external dangers. The bigger events
happen less frequently. By growing sufficiently rapidly it has a
finite chance of surviving forever. Even the eventual collapse or
heat death of the universe might be evaded or survived if an entity
can restructure itself properly.
The human race will expand into the solar system soon, and
Gerry O'Neill's little Earths will be part of it. But the economics
of automation will become very persuasive in space even before
machines achieve human competence.
I visualize immensely lucrative self-reproducing robot
factories in the asteroids. Solar powered machines would prospect and
deliver raw materials to huge, unenclosed, automatic processing
plants. Metals, semiconductors and plastics produced there would be
converted by robots into components which would be assembled into
other robots and structural parts for more plants. Machines would be
recycled as they broke. If the reproduction rate is higher than the
wear out rate, the system will grow exponentially. A small fraction of
the output of materials, components, and whole robots could make
someone very, very rich.
The first space industries will be more conventional. Raw
materials purchased from Earth or from human space settlements will be
processed by human supervised machines and sold at a profit. The high
cost of maintaining humans in space insures that that there will
always be more machinery per person there than on Earth. As machines
become more capable, the economics will favor an ever higher
machine/people ratio. Humans will not necessarily become fewer, but
the machines will multiply faster.
When humans become unnecessary in space industry, the
machines' physical growth rate will climb. When machines reach and
surpass humans in intelligence, the intellectual growth rate will rise
similarly. The scientific and technical discoveries of
super-intelligent mechanisms will be applied to making themselves
smarter still. The machines, looking quite unlike the machines we
know, will explode into the universe, leaving us behind in a
figurative cloud of dust. Our intellectual, but not genetic, progeny
will inherit the universe. Barring prior claims.
This may not be as bad as it sounds, since the machine
civilization will certainly take along everything we consider
important, including the information in our minds and genes. Real
live human beings, and a whole human community, could be reconstituted
if an appropriate circumstance ever arose. Since we are biologically
committed to personal death, immortal only through our children and
our culture, shouldn't we rejoice to see that culture become as robust
as possible?
An Alternative
Some of us have very egocentric world views. We anticipate the
discovery, within our lifetimes, of methods to extend human lifespans,
and look forward to a few eons of exploring the universe. We don't
take kindly to being upstaged by our creations.
The machines' major advantage is their progress rate. We
evolve by DNA + nucleated cell + sex + personal death, they develop by
the much faster intelligence + language + culture + science +
technology technique. If we could somehow learn the new way, we might
be able hold our own.
Genetic engineering is an option. Successive generations of
human beings could be designed by mathematics, computer simulations,
and experimentation, like airplanes and computers are now. But this
is just building robots out of protein. Away from Earth, protein is
not an ideal material. It's stable only in a narrow temperature and
pressure range, is sensitive to high energy disturbances, and rules
out many construction techniques and components. Anyway, second rate
superhuman beings are just as threatening as first rate ones, whatever
they're made of.
What's really needed is a process that gives an individual all
the advantages of the machines, at small personal
cost. Transplantation of human brains into manufactured bodies has
some merit, because the body can be matched to the environment. It
does nothing about the limited and fixed intelligence of the brain,
which the artificial intellects will surpass.
Transmigration
You are in an operating room. A robot brain surgeon is in
attendance. By your side is a potentially human equivalent computer,
dormant for lack of a program to run. Your skull, but not your brain,
is anaesthetized. You are fully conscious. The surgeon opens your
brain case and peers inside. Its attention is directed at a small
clump of about 100 neurons somewhere near the surface. It determines
the three dimensional structure and chemical makeup of that clump
non-destructively with neutron tomography, phased array radio
encephalography, and ultrasonic radar. It writes a program that
models the behavior of the clump, and starts it running on a small
portion of the computer next to you. Fine wires are run from the
edges of the neuron assembly to the computer, providing the simulation
with the same inputs as the neurons. You and the surgeon check the
accuracy of the simulation. After you are satisfied, tiny relays are
inserted between the edges of the clump and the rest of the brain.
Initially these leave brain unchanged, but on command they can connect
the simulation in place of the clump. A button which activates the
relays when pressed is placed in your hand. You press it, release it
and press it again. There should be no difference. As soon as you are
satisfied, the simulation connection is established firmly, and the
now unconnected clump of neurons is removed.
The process is repeated over and over for adjoining clumps,
until the entire brain has been dealt with. Occasionally several
clump simulations are combined into a single equivalent but more
efficient program. Though you have not lost consciousness, or even
your train of thought, your mind (some would say soul) has been
removed from the brain and transferred to a machine.
In a final step your old body is disconnected. The computer is
installed in a shiny new one, in the style, color and material of your
choice. You are no longer a cyborg halfbreed, your metamorphosis is
complete.
Advantages become instantly apparent. Your computer has a
control labelled speed. It had been set to slow, to keep the
simulations synchronized with the old brain, but now you change it to
fast. You can communicate, react and think a thousand times faster.
But that's just a start.
The program in your machine can be read out and altered,
letting you conveniently examine, modify, improve and extend yourself.
The entire program may be copied into similar machines, giving two or
more thinking, feeling versions of you. You may choose to move your
mind from one computer to another more technically advanced, or more
suited to a new environment. The program can also be copied to some
future equivalent of magnetic tape. If the machine you inhabit is
fatally clobbered, the tape can be read into an blank computer,
resulting in another you, minus the experiences since the copy. With
enough copies, permanent death would be very unlikely.
As a computer program, your mind can travel over information
channels. A laser can send it from one computer to another across
great distances and other barriers. If you found life on a neutron
star, and wished to make a field trip, you might devise a way to build
a neutron computer and robot body on the surface, then transmit your
mind to it. Nuclear reactions are a million times quicker than
chemistry, so the neutron you can probably think that much faster. It
can act, acquire new experiences and memories, then beam its mind back
home. The original body could be kept dormant during the trip to be
reactivated with the new memories when the return message arrived.
Alternatively, the original might remain active. There would then be
two separate versions of you, with different memories for the trip
interval.
Two sets of memories can be merged, if mind programs are
adequately understood. To prevent confusion, memories of events would
indicate in which body they happened. Merging should be possible not
only between two versions of the same individual but also between
different persons. Selective mergings, involving some of the other
person's memories, and not others would be a very superior form of
communication, in which recollections, skills, attitudes and
personalities can be rapidly and effectively shared.
Your new body will be able to carry more memories than your
original biological one, but the accelerated information explosion
will insure the impossibility of lugging around all of civilization's
knowledge. You will have to pick and choose what your mind contains
at any one time. There will often be knowledge and skills available
from others superior to your own, and the incentive to substitute
those talents for yours will be overwhelming. In the long run you
will remember mostly other people's experiences, while memories you
originated will be floating around the population at large. The very
concept of you will become fuzzy, replaced by larger, communal egos.
Mind transferral need not be limited to human beings. Earth
has other species with brains as large, from dolphins, our cephalic
equals, to elephants, whales, and giant squid, with brains up to
twenty times as big. Translation between their mental representation
and ours is a technical problem comparable to converting our minds
into a computer program. Our culture could be fused with theirs, we
could incorporate each other's memories, and the species boundaries
would fade. Non-intelligent creatures could also be popped into the
data banks. The simplest organisms might contribute little more than
the information in their DNA. In this way our future selves will
benefit from all the lessons learned by terrestrial biological and
cultural evolution. This is a far more secure form of storage than
the present one, where genes and ideas are lost when the conditions
that gave rise to them change.
Our speculation ends in a super-civilization, the synthesis of
all solar system life, constantly improving and extending itself,
spreading outwards from the sun, converting non-life into mind. There
may be other such bubbles expanding from elsewhere. What happens when
we meet? Fusion of us with them is a possibility, requiring only a
translation scheme between the memory representations. This process,
possibly occuring now elsewhere, might convert the entire universe
into an extended thinking entity, a prelude to even greater things.